文章基本信息

标题：Large Deviations Theory and Empirical Estimator Choice
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作者：Grendar, Marian ; Judge, George G.
期刊名称：Journal of Food Distribution Research
印刷版ISSN：0047-245X
出版年度：2006
卷号：37
期号：SUPPL
出版社：Food Distribution Research Society
摘要：Criterion choice is such a hard problem in information recovery and in estimation and inference. In the case of inverse problems with noise, can probabilistic laws provide a basis for empirical estimator choice? That is the problem we investigate in this paper. Large Deviations Theory is used to evaluate the choice of estimator in the case of two fundamental situations-problems in modelling data. The probabilistic laws developed demonstrate that each problem has a unique solution-empirical estimator. Whether other members of the empirical estimator family can be associated a particular problem and conditional limit theorem, is an open question.